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Record W4381308151 · doi:10.2147/jpr.s411923

Skin Temperature of Acupoints in Health and Primary Dysmenorrhea Patients: A Systematic Review and Meta-Analysis

2023· review· en· W4381308151 on OpenAlexaboutno aff
Xuesong Wang, Guang Zuo, Jun Liu, Juncha Zhang, Xuliang Shi, Xisheng Fan, Xuxin Li, Yuanbo Gao, Hao Chen, Cun‐Zhi Liu, Yan-Fen She

Bibliographic record

VenueJournal of Pain Research · 2023
Typereview
Languageen
FieldMedicine
TopicInfrared Thermography in Medicine
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsMedicineChecklistSkin temperatureMeta-analysisInternal medicineSignificant differenceMean differencePhysical therapyConfidence intervalDermatology

Abstract

fetched live from OpenAlex

Objective: Dysmenorrhea is a common clinical condition and some studies shown that the skin temperature of some acupoints changes in primary dysmenorrhea (PD) patients. This study aimed to evaluate the changes in skin temperature at specific acupoints in PD patients and healthy subjects. Methods: The literature for assessing skin temperature at acupoints in PD patients and healthy subjects was searched in eight databases. The literatures obtained from the search was independently screened by two authors, and the quality of the included articles was evaluated using the consensus checklist of the Thermographic Imaging in Sports and Exercise Medicine (TISEM) and the Newcastle-Ottawa Scale (NOS) scale. The skin temperature of the relevant acupoints or the difference between the left and right acupoints of the same name was used as the outcome during any period of menstruation. Finally, the meta-analysis was performed using RevMan 5.4.1 software to evaluate the changes in skin temperature in the related acupoints. Results: Seven eligible studies were included, which included 328 patients with PD and 279 healthy subjects. The results of the meta-analysis revealed a significant difference in skin temperature around the Sanyinjiao (SP6)(MD: 0.04, 95% CI: 0.00, 0.08), Xuehai (SP 10)(MD: -0.07, 95% CI:-0.11, -0.02) and Taixi (KI 3)(MD: 0.06, 95% CI:0.01, 0.11) acupoints between PD and healthy subjects. PD patients also showed a difference in skin temperature at the Taixi (KI 3)(MD: 0.14, 95% CI:0.04, 0.24), Shuiquan (KI 5)(MD: 0.11, 95% CI: 0.03,0.19), Taichong (LR 3)(MD: -0.10, 95% CI: -0.19,-0.01), Diji (SP 8)(MD: -0.09, 95% CI: -0.16, -0.01), and Xuehai (SP 10)(MD: -0.14, 95% CI: -0.23, -0.06) acupoint areas at different times of menstruation compared to that of healthy subjects, as revealed by the subgroup analysis. Conclusion: Primary dysmenorrhea patients showed some differences in the skin temperature of the special acupoints are as Sanyinjiao (SP6), Diji (SP 8), Xuehai (SP 10), Shuiquan (KI 5), Taichong (LR 3), and Taixi (KI 3) compared with healthy subjects. Registration Number: CRD42022381387.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.014
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.020
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0140.031
Bibliometrics0.0050.007
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.173
GPT teacher head0.480
Teacher spread0.307 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2023
Admission routes1
Has abstractyes

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